• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.225-229
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• 1998

If there is a mismatch between the controller programmed rotor time constant and the actual time constant of motor, the decoupling between the flux and torque is lost in an indirect rotor field oriented control. This paper presents a new estimation scheme for rotor time constant using artificial neural networks. The parameters of induction motor model organize 2 layer neural to be weight between neuron, which is proposed new in this paper. This method makes networks simple, so its brings not only the improvement in speed but simplification in calculation. Furthermore, it is possible to estimated rotor time constant real time through on-line learning without using off-line learning. The digital simulation and the experimental results to verify the effectiveness of the new method are described in this paper.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.600-602
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• 1995

The paper presents neural network control techniques for load frequency control of two area power system. Using learning algorithm of error back propagation after learning accept input on the optimal control $e_{i}$, $\dot{e}_{i}$, and $u_{i}$ frequency characteristic and tie-line load flow characteristic investigated dynamic. From result simulation, frequency deviation and tie-line load flow deviation have reduction remarkable.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.124-129
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• 2003

In the face of global competitor the requirements flor the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models fir simulation and quantitative description of the industrial operations involved. In this paper, a on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Korean Journal of Health Education and Promotion
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• v.21 no.3
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• pp.151-177
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• 2004

Recently, the educational community has attempted to implement the theory of multiple intelligences. In approaching multiple intelligences, teachers have applied the same structural approach which has been so successful with cooperative learning. Cooperative learning is easy to learn and implement, fun for teachers and students, and produce profoundly positive outcomes along a remarkable number of dimensions. Different structures are designed for different outcomes, including enhanced mastery of subject matter, improved thinking skills, team building, class building, development of social character and social skills, communication skills, classroom management, classroom discipline, and development of and engagement of each of the multiple intelligences. Cooperative learning is becoming an increasingly popular teaching strategy. In this study, it is aimed to clarify the application of cooperative learning in health education. Cooperative Learning in health education enhances student learning by: 1) providing a shared cognitive set of information between students, 2) motivating students to learn the material, 3) ensuring that students construct their own health knowledge, 4) providing formative feedback, 5) developing social and health group skills necessary for success outside the classroom, and 6) promoting positive interaction between members of different cultural and socio-economic groups. Cooperative Learning structures and techniques in health education are following. Flash Card, Focused Listing, Structured Problem-solving, Paired Annotations, Structured Learning Team Group Roles, Send-A-Problem, Value Line, Uncommon Commonalities, Team Expectations, Double Entry Journal, Guided Reciprocal Peer Questioning, What if. Because the purpose of health education is the practice, therefore health specialists have to guide powerful and effective teaching method The application of cooperative learning in health education may improve its effectiveness.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.521-536
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• 2006

The Blended Learning of K-12 education can he complimented to exceed the limits of the traditional face-to-face instructional method and can help learners have experiences with both various interactions and different learning experiences. Specifically, in K-12 education blended learning has a strength in being able to integrate on-line instruction with off-line instruction and actively help learners emerge with a breadth of knowledge gained collaboratively.<중략>For the objective of the study, that is, an investigation by a literature review process, the mode) of the process of collaboratively emerging knowledge as well as the alternative model of the concept can be applied as a developmental research method, which can improve practical procedure, process, and prescription. For overcoming the model and the real situation, this study was applied with Checkland(1999)'s soft system methodology, using$\square$the comparison of the model and real situations$\square$part and$\square$defining the alternatives$\square$of Checkland(1999)'s methods. In conclusion, analyzing the conceptual model and real situation helps in the development of a model which can minimize the discrepancy between the conceptual model and the real situation within K-12 education.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.137-141
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• 2003

LS-SVM(least squares support vector machine) is a widely applicable and useful machine learning technique for classification and regression analysis. LS-SVM can be a good substitute for statistical method but computational difficulties are still remained to operate the inversion of matrix of huge data set. In modern information society, we can easily get huge data sets by on line or batch mode. For these kind of huge data sets, we suggest an on line pruning regression method by LS-SVM. With relatively small number of pruned support vectors, we can have almost same performance as regression with full data set.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.213-216
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• 2006

During the last decade several different methods have been proposed for the estimation of thermal deformations in the line heating process. These are mainly based on the assumption of residual strains in the heat-affected zone or simulated relations between heating conditions and residual deformations. However these results were restricted in the application from the too simplified heating conditions or the shortage of the data. The purpose of this paper is to develop a simulator of thermal deformation in the line heating using the artificial neural network. Two neural network predicting the maximum temperature and deformations at the heating line are studied. Deformation data from the line heating experiments are used for learning data for the network. It was observed that thermal deformation predicted by the neural network correlate well with the experimental result.

• Research in Mathematical Education
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• v.21 no.1
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• pp.1-13
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• 2018

While the utility of the number line is considerable, articulating its conceptual foundation is often neglected in school mathematics. We suggest that it is important to build up strong conceptual foundations in the earlier grades so that number lines can be used in a more meaningful way and that any misconceptions associated with the number line can be prevented or intervened. This paper addresses unit, direction, and origin as the key elements of number lines and presents activities from Davydov's curriculum for early grades that promote exploration of those key elements and may resolve some students' misconceptions. As shown in sample activities from Davydov's curriculum, this paper suggests that students can broaden their perspectives on the number line and use it versatilely in various areas of mathematics learning when they deeply engage in the construction of a number line and have flexibility in interpreting the relationships between key number line elements.

• Research in Mathematical Education
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• v.26 no.4
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• pp.271-289
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• 2023

This research investigates the development of elementary students' concepts of line segments, straight lines, and rays, employing metaphor analysis as a research methodology. By analyzing metaphorical expressions, the research aims to explore how elementary students form these geometric concepts line segments, straight lines, and lays and evolve their understanding of them across different grades. Surveys were conducted with elementary school students in grades three to six, focusing on metaphorical expressions and corresponding their reasons associated with line segments, straight lines, and rays. The data were analyzed through coding and categorization to identify the types in students' metaphorical expressions. The analysis of metaphorical expressions identified five types: straightness, infinity or direction, connections of another geometric concepts, shape and symbols, and terminology.

• Journal of Convergence for Information Technology
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• v.10 no.11
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• pp.195-201
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• 2020

There have been many developments and innovations in the educational environments in line with the rapidly evolving information age. E-Learning is a representative example of this rapid evolution. However, E-Learning is challenging to maintain students' concentration because of the low engagement level and limited interactions between instructors and students. Additionally, instructors have limitations in identifying learners' concentration. This paper proposes a system that can measure E-learning users' concentration levels by detecting the users' eyelid movement and the top of the head. The system recognizes the eyelid and the top of the head and measures the learners' concentration level. Detection of the eyelid and the top of the head triggers an event to assess the learners' concentration level based on the users' response. After this process, the system provides a normalized concentration score to the instructor. Experiments with experimental groups and control groups were conducted to verify and validate the system, and the concentration score showed more than 90% accuracy.